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fixed typo in opencv_stitching

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This commit is contained in:
Alexey Spizhevoy 2011-06-17 13:22:38 +00:00
parent 0ec452c152
commit 3be51ded5d
1 changed files with 77 additions and 77 deletions
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154
modules/stitching/autocalib.cpp
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@ -38,80 +38,80 @@
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "autocalib.hpp"
#include "util.hpp"
using namespace std;
using namespace cv;
void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
{
CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));
const double* h = reinterpret_cast<const double*>(H.data);
double d1, d2; // Denominators
double v1, v2; // Focal squares value candidates
f1_ok = true;
d1 = h[6] * h[7];
d2 = (h[7] - h[6]) * (h[7] + h[6]);
v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;
v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;
if (v1 < v2) swap(v1, v2);
if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
else if (v1 > 0) f1 = sqrt(v1);
else f1_ok = false;
f0_ok = true;
d1 = h[0] * h[3] + h[1] * h[4];
d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];
v1 = -h[2] * h[5] / d1;
v2 = (h[5] * h[5] - h[2] * h[2]) / d2;
if (v1 < v2) swap(v1, v2);
if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
else if (v1 > 0) f0 = sqrt(v1);
else f0_ok = false;
}
void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches,
vector<double> &focals)
{
const int num_images = static_cast<int>(features.size());
focals.resize(num_images);
vector<double> all_focals;
for (int i = 0; i < num_images; ++i)
{
for (int j = 0; j < num_images; ++j)
{
const MatchesInfo &m = pairwise_matches[i*num_images + j];
if (m.H.empty())
continue;
double f0, f1;
bool f0ok, f1ok;
focalsFromHomography(m.H, f0, f1, f0ok, f1ok);
if (f0ok && f1ok)
all_focals.push_back(sqrt(f0 * f1));
}
}
if (static_cast<int>(all_focals.size()) < num_images - 1)
{
LOGLN("Can't estimate focal length, will use anaive approach");
double focals_sum = 0;
for (int i = 0; i < num_images; ++i)
focals_sum += features[i].img_size.width + features[i].img_size.height;
for (int i = 0; i < num_images; ++i)
focals[i] = focals_sum / num_images;
}
else
{
nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());
for (int i = 0; i < num_images; ++i)
focals[i] = all_focals[all_focals.size()/2];
}
}
//M*/
#include "autocalib.hpp"
#include "util.hpp"
using namespace std;
using namespace cv;
void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
{
CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));
const double* h = reinterpret_cast<const double*>(H.data);
double d1, d2; // Denominators
double v1, v2; // Focal squares value candidates
f1_ok = true;
d1 = h[6] * h[7];
d2 = (h[7] - h[6]) * (h[7] + h[6]);
v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;
v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;
if (v1 < v2) swap(v1, v2);
if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
else if (v1 > 0) f1 = sqrt(v1);
else f1_ok = false;
f0_ok = true;
d1 = h[0] * h[3] + h[1] * h[4];
d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];
v1 = -h[2] * h[5] / d1;
v2 = (h[5] * h[5] - h[2] * h[2]) / d2;
if (v1 < v2) swap(v1, v2);
if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
else if (v1 > 0) f0 = sqrt(v1);
else f0_ok = false;
}
void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches,
vector<double> &focals)
{
const int num_images = static_cast<int>(features.size());
focals.resize(num_images);
vector<double> all_focals;
for (int i = 0; i < num_images; ++i)
{
for (int j = 0; j < num_images; ++j)
{
const MatchesInfo &m = pairwise_matches[i*num_images + j];
if (m.H.empty())
continue;
double f0, f1;
bool f0ok, f1ok;
focalsFromHomography(m.H, f0, f1, f0ok, f1ok);
if (f0ok && f1ok)
all_focals.push_back(sqrt(f0 * f1));
}
}
if (static_cast<int>(all_focals.size()) >= num_images - 1)
{
nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());
for (int i = 0; i < num_images; ++i)
focals[i] = all_focals[all_focals.size()/2];
}
else
{
LOGLN("Can't estimate focal length, will use naive approach");
double focals_sum = 0;
for (int i = 0; i < num_images; ++i)
focals_sum += features[i].img_size.width + features[i].img_size.height;
for (int i = 0; i < num_images; ++i)
focals[i] = focals_sum / num_images;
}
}